Access Layer Research Articles

Security Model for the Detection of Distributed Denial of Service Attack (DDoS) at the Access Layer in Cloud Reference Architecture

DDoS attacks on the cloud have become an emerging problem, which calls for an intelligent protection solution for information, communication and computing resources. Cloud reference architecture as a new technology with wider access facility, the access layer in the reference architecture becomes grave to numerous security challenges, and it is mostly exploited by the attacker using compromised computers to launch DDoS attack which affects its performance by shutting down some services. Many security frameworks have been proposed in the past, but they are not enough to provide security solution for accurate detection and control of DDoS attack at the access layer. Intelligent security model based on artificial neural network was developed to detect and control DDoS attack at the access layer. DDoS dataset obtained online was used to train and test the intelligent security model using MATHLAB workspace. Simulated results implemented and generated with receive operator characteristic analyzer (Roc) showed a true positive rate of 98.2% to detect and control DDoS attack at the access layer and a false negative rate of 0.02%. The inclusion of additional parameters to determined and identifies the source of the attack, whether it is lunch from outside or inherent within the reference architecture is recommended. KEYWORDS: Reference Architecture, Access Layer, Distributed Denial of Service (DDOS), Artificial Neural Network’s (ANN’s)

Application of Industry 4.0 and digital twin in the field of smart healthcare

There is an increasing need for preventive health care as well as precise diagnosis and tailored treatment of different diseases in recent years. Providing customized treatment for each patient and maximizing accuracy and efficiency are main goals of a good healthcare system. This thesis explores the integration of digital twin technology with Industry 4.0 in healthcare. Digital twins create virtual representations of physical systems, enabling real-time monitoring and tailored treatments. Key elements include the living human body, IoT, digital twin, cloud computing, and simulation. The architecture comprises data acquisition, data munging, data storage, data simulation with analytics, and user access layers. Creating a digital twin involves precise 3D modeling, representing the entire body or specific organs. A case study demonstrates real-time monitoring using wearable sensors for blood pressure, blood sugar, and heart rate. Data is transmitted, integrated with the digital twin, and accessible via a website with alarms for abnormal readings. While Industry 4.0 and digital twin adoption in healthcare is evolving, the architecture serves as a reference. It offers real-time data for diagnosis and treatment, with potential for advanced simulations. Challenges include automated data systems and privacy concerns. Despite limitations, this integration holds promise for precision medicine and personalized healthcare.

Large-scale hydropower dispatching system based on cloud platform and its key technologies

In the past decade, the rapid expansion of hydropower capacity in China brings challenges to hydropower dispatching in data management and operation scheduling. In data management, the scale of hydropower operation data increases explosively, presenting typical big data features. In operation scheduling, the optimization of hydropower system operations is a high-dimension, nonconvex, and nonlinear problem. Conventional optimization methods encounter the “dimensionality disaster”, and cannot solve the scheduling problem efficiently. To deal with these challenges, by analyzing the data characteristics and operation scheduling requirements, this paper develops a large-scale hydropower dispatching system based on the cloud platform. The dispatching system consists of four layers: data access layer, cloud platform layer, data sharing layer, and application layer, which has good scalability and flexibility in data management and operation scheduling. In the application layer, key technologies based on the big data and cloud computing resources of the dispatching system are proposed to carry out the optimal operation of hydropower systems, including distributed parallel dynamic programming (DPDP) for long-/medium-term scheduling and data mining-based method (DMM) for short-term scheduling. Finally, the dispatching system is applied to the operation of hydropower systems in southwest China. Results indicate that: 1) The developed dispatching system is capable of processing 18 million data records per day, with a peak processing speed of 10,000 data requests per second, fulfilling the requirements for hydropower dispatching. 2) In long-term generation scheduling, under varying levels of runoff and plant scales, DPDP has demonstrated a remarkable reduction in computing time compared to dynamic programming, obtaining the same optimal solution with over 90 % less computational time. 3) In short-term peak shaving operation, on typical dry and wet days, the computing time of DMM is 7.2 s and 7.5 s, respectively, far less than the time of mixed-integer linear programming, and the maximum residual load obtained by DMM is lower than historical observations, indicating its effectiveness.

“I just want to annoy him now and say, look, I can do STEM too!”: a qualitative investigation into the attitudes and engagement of female students in STEM education in Ireland

ABSTRACT Women are underrepresented in STEM (Science, Technology, Engineering and Maths); with further stratification existing for those from low socio-economic backgrounds. Understanding the reasons for this is essential to progress towards equality in STEM fields. This paper takes the perspective of such marginalized groups and explores their beliefs about STEM within a school-based system, for the purposes of this study a focus has been placed on gender and socio-economic status. Focus groups were conducted with 18 female participants attending Irish secondary schools. The results provide insight into the challenges faced when pursuing STEM; additionally, the motivating and inhibiting factors are reported. Results reveal how social and academic barriers prevent young women from progressing in STEM, highlighting how intersectional layers of disadvantage limit equal access in STEM education. Such findings can inform the development of policies to help students access STEM-education, especially those attending schools characterized by higher concentrations of students from low-socio-economic backgrounds.

PENGGUNAAN ALGORITMA GEOSHASHING DALAM PENCARIAN LETAK INFORMASI GEOGRAFIS PENGGANTI KOOORDINAT LATITUDE DAN LONGITUDE

In the digital age when the search for geographic data is becoming increasingly important in location applications, including mapping, navigation, and analysis of the environment of a place within a location. Geohashing algorithms offer an efficient approach to encoding and storing geographic data in string format, these strings use alphanumeric generated by geohashing of numbers and letters in the search for location points by coordinates, it can also offer an access layer of sensitive location data. This study aims to explore the application of geohashing algorithms in geographic data management. Geohashing algorithm in the search for the location of geographic information as an alternative to latitude and longitude coordinates. In particular, this study analyzes the efficiency of geohashing in data compression, the localization accuracy of geohashing use allows for better grouping of geographic data, and supports spatial data search such as location search and coordinate point search within a specific region. Geohashing algorithms are implemented in geographic data and tested for various search scenarios. From the results of the study showing that geohashing can significantly increase the speed of searching for geographic information, the geohashing algorithm proves its action as an effective tool in the management and search of geographic data, in the search for location coordinate data, it can also provide an alternative to get the latitude and longitude of a location. The results show that geohashing can significantly increase the speed of searching for geographic information, especially in reaching a location with a small and large data box grid level according to the entered string characters. The use of geohashing not only improves the efficiency and speed of searches but also provides additional benefits in terms of the management and protection of geographic data. Testing on this system is carried out by providing geographic access to the location application API that has been created on demand to obtain geographic data information and location points.

A read-efficient and write-optimized hash table for Intel Optane DC Persistent Memory

Emerging non-volatile memory technologies are driving the next generation of storage systems and durable data structures. Among them, many hash table proposals employ NVM as the storage layer for both fast access and efficient persistence. Most of them are based on the assumption that NVM has cacheline access granularity, poor write endurance, DRAM-comparable read latency and relatively higher write latency. However, a commercial non-volatile memory product, namely Intel Optane DC Persistent Memory (Optane), has some interesting features that are different from previous assumptions, such as 256-byte OptaneLine access granularity, higher read latency than DRAM and DRAM-comparable write latency, limited read/write bandwidth, and hardware-layer wear-leveling. Confronted with the new challenges brought by Optane, we propose Rewo-Hash, a novel read-efficient and write-optimized persistent hash table. Our incremental contributions over our previous work are summarized as follows. First, provide a more detailed technical description for cached table-inclined read mechanism and log-free atomic write mechanism. Second, we devise a consistent shadowing synchronization scheme to mask the data synchronization overhead. Third, we propose a non-blocking lightweight resizing scheme and elaborate the crash recovery mechanism. Fourth, we conduct a comprehensive analysis of the implications of Intel ceasing the production of Optane, and provide a forward-looking perspective on the future of non-volatile memory. The experimental results show that compared with state-of-the-art NVM-Optimized hash tables, Rewo-Hash gains remarkable performance improvement.

Defect Density and Atomic Defect Recognition in the Middle Layer of a Trilayer MoS2 Stack.

Molybdenum disulfide (MoS2) is one of the most intriguing two-dimensional materials, and moreover, its single atomic defects can significantly alter the properties. These defects can be both imaged and engineered using spherical and chromatic aberration-corrected high-resolution transmission electron microscopy (CC/CS-corrected HRTEM). In a few-layer stack, several atoms are vertically aligned in one atomic column. Therefore, it is challenging to determine the positions of missing atoms and the damage cross-section, particularly in the not directly accessible middle layers. In this study, we introduce a technique for extracting subtle intensity differences in CC/CS-corrected HRTEM images. By exploiting the crystal structure of the material, our method discerns chalcogen vacancies even in the middle layer of trilayer MoS2. We found that in trilayer MoS2 the middle layer's damage cross-section is about ten times lower than that in the monolayer. Our findings could be essential for the application of few-layer MoS2 in nanodevices.

Determining peat's vertical hydraulic diffusivity and hydraulic conductivity from naturally occurring hydraulic pressure fluctuations measured at various depths

AbstractThis study presents a method that could be used to assess the in‐situ saturated vertical hydraulic conductivity of deeper and more decomposed peat layers. Deeper peat layers may exhibit very low permeability comparable to clayey sediments, where measurements and sediment sample collection are very difficult. More traditional measurement methods, such as slug‐tests and permeameter tests, have proven difficult to carry out in these conditions, necessitating an alternative method. For surpassing these possible constraints, this paper introduces a field method to quantify vertical hydraulic diffusivity, capitalizing on naturally occurring hydraulic pressure fluctuations measured with buried pressure sensors. The determined diffusivity values are used to calculate vertical hydraulic conductivity of peat using separately measured compressibility and specific storage values. Our research demonstrates the feasibility of using this method to evaluate vertical hydraulic diffusivity in lower peat layers. Calculated diffusivity values, combined with peat compressibility measurements, yield reasonable estimates of vertical hydraulic conductivity for dense fen peat comparable with more widely used in‐situ and laboratory methods. It also shows potential for vertical hydraulic characteristics parametrization in the upper less decomposed and compacted peat layers; however, further research is needed to understand the method's limitations in such conditions. Our approach provides a potential method for measuring in‐situ vertical hydraulic properties of less accessible peat layers, often overlooked, while also providing a way to surpass the scale‐dependency constraints inherent in peatlands' heterogeneous structure. Such information is necessary when studying the hydraulic interactions between groundwater aquifers and peatlands.

Cooperative MAC Protocol based on Best Data Rate (CMAC-DR)

As wireless signals are broadcast in nature, which implies that, a broadcast communication purposive to a predetermined destination may be received by a non-intended intermediate station. Cooperative transference, which employ interposed stations to pass on the eavesdropped data to attain the contrast gains, has a substantial capability to revamp the channeling effectiveness in wireless systems. In this it is evident that having cooperation amid stations in a wireless system can accomplish higher throughput with enhanced network lifetime. Proffered work bestows a model for medium access layer called Cooperative MAC protocol based on optimal Data Rate (CMAC-DR). In the proffered work, stations with more data rate aid stations having lesser data rate in their communication by redirecting their congestion. In CMAC-DR model, utilizing the conveyance of eavesdropped information, potential helper stations with more data rate Send out Helper Ready to Send (HRTS), the stations with less data rate maintains a table, called Co-op table of potential helper stations, that can aid in its transmissions. During communication, the source station with low data rate chooses either transmitting by the way of a helper station, so that it lowers the end to end transference delay and increases the throughput or opt only direct transmission, if no potential helper is found or if CMAC-DR becomes an overhead. By analyzing varied simulated scenarios, CMAC-DR evaluates the elevation in the overall network lifetime, throughput and minimization of delay. The CMAC-DR protocol is unambiguous and in accordant with legacy 802.11 also when compared to this, we find improved performance in terms of delay throughput and network lifetime since data rate is considered as relay selection condition.

Storage and other considerations for enterprise digital asset management solutions

Five years after the launch of an enterprise digital asset management (DAM) solution in a US university setting, how has it been adopted on campus? Is the solution still meeting the customer requirements? This paper addresses these questions by examining the DAM solution implemented at the University of Notre Dame. It delves into the storage component, especially in the context of recent shifts that have marked the end of the era of unrestricted and complimentary storage for higher education. The examination extends to the broader campus DAM solution space, analysing its current level of adoption. It emphasises the necessity for an effective governance structure and communications, and contends that DAM software vendors should take into consideration the distributed nature of higher education institutions. At the core of addressing these challenges is a proposed architectural redesign that separates core DAM functions from specialist features, with shared storage and access layers to improve efficiency and facilitate the breakdown of silos.

Design of emergency evacuation route for large buildings based on cloud computing and GIS big data

In order to ensure the safety of life and property in large buildings, the design of emergency evacuation routes for large buildings based on cloud computing and GIS big data is studied. Combining cloud computing and GIS big data, a command model for emergency evacuation of large buildings is built. Emergency evacuation functions are realized through the access layer, business logic layer, cloud computing layer and data layer. GIS big data of large buildings is stored in the model data layer. GIS geographic data is clustered through the MapReduce based parallel K-means clustering algorithm in the cloud computing layer. After clustering, the emergency evacuation road network of large buildings is constructed through GIS in the business logic layer. On the road network, the emergency evacuation route selection method combining Dikstra algorithm and ant colony algorithm is used to realize the optimal route selection of emergency evacuation of large buildings. Experiments show that this method can effectively select the best evacuation path in large buildings, and the evacuation speed of the selected path is fast, which can ensure the safety of people in buildings.

A Torpor-based Enhanced Security Model for CSMA/CA Protocol in Wireless Networks

Mobile wireless networks enable the connection of devices to a network with minimal or no infrastructure. This comes with the advantages of ease and cost-effectiveness, thus largely popularizing the network. Notwithstanding these merits, the open physical media, infrastructural-less attributes, and pervasive deployment of wireless networks make the channel of communication (media access) vulnerable to attacks such as traffic analysis, monitoring, and jamming. This study designed a virtual local area network (VLAN) model to circumvent virtual jamming attacks and other intrusions at the Media Access Control (MAC) layer of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. A Torpor VLAN (TVLAN) Data Frame Encapsulation and the algorithm for T-VLAN security in CSMA/CA were formulated and presented. A simulation experiment was conducted on the model using OMNeT++ software. The performance metrics used to evaluate the model were packet delivery ratio, network throughput, end-to-end channel delay, and channel load. The simulation results show that the TVLAN defence mechanism did not increase the channel load arbitrarily during TVLAN defence. similarly, the system throughput was shown to be 82% during TVLAN defence. Nevertheless, the network delay of the system during TVLAN defence was significantly high but the channel load was 297 when the TVLAN security mechanism was launched. These results demonstrate the model’s ability to provide a survivability mechanism for critical systems when under attack and add a security layer to the CSMA/CA protocol in wireless networks. Such a remarkable performance is required of a CSMA/CA infrastructure for improving the cybersecurity posture of a wireless network.

Evaluation of Efficacy of MV Loop for En masse Anterior Retraction as Compared to Opus and Snail Loop Using Finite Element Method and Clinical Intervention: A Research Protocol

Abstract Background: In orthodontics, space closure after extraction is crucial. Frictionless mechanics in preadjusted “edgewise appliance” treatment in orthodontics are better alternatives to friction mechanics. The major benefit is dissipation of force, a high M: F ratio and a low load-deflection rate which is not there in friction mechanics. The retraction loops are Snail loop, Opus loop, K Sir loop, L loop etc. which are used as force system in frictionless mechanics. Objectives: To evaluate and compare the efficacy of Multiple Variability (MV) loop for qualitative and quantitative en masse anterior retraction as compared to Opus and Snail loop. Materials and Methods: The study will be carried out in the Department of Orthodontics and Dentofacial Orthopaedics, Sharad Pawar Dental College, Sawangi (M), Wardha with the technical assistance from NIT Engineering College, Pune. MV loop, Opus loop and Snail loop will be fabricated in “0.019 × 0.025, 0.017 × 0.025 inch Titanium Molybdenum alloy (TMA) and 0.017 × 0.025 inch Stainless Steel (SS) wire” with 1 and 2 mm preactivation bends will be analysed on Finite element method (FEM) Software. Then clinical trials will be carried out based on qualitative and quantitative assessment of records for evaluation of MV loop, opus loop and Snail loop. Expected Results: The FEM analysis and clinical trials will predict the perfect design of loop with adequate preactivation bends. Mainly on data access layer (DHAL) analysis MV loop showed 10:1 Moment to Force (M:F). Similar results are expected on FEM analysis and clinical trials. MV loop will show superior results as compared to Opus and Snail loop. Conclusion: Loop mechanics provide efficient intrusion and retraction in extraction cases. A loop to be effective and efficient needs to clinically as well as mechanically evaluated. MV loop was fabricated to fulfill all the requirements of loop. Clinical evaluation of loop will provide complete effectiveness of loop.

Flare: An FPGA-Based Full Precision Low Power CNN Accelerator with Reconfigurable Structure.

Convolutional neural networks (CNNs) have significantly advanced various fields; however, their computational demands and power consumption have escalated, posing challenges for deployment in low-power scenarios. To address this issue and facilitate the application of CNNs in power constrained environments, the development of dedicated CNN accelerators is crucial. Prior research has predominantly concentrated on developing low precision CNN accelerators using code generated from high-level synthesis (HLS) tools. Unfortunately, these approaches often fail to efficiently utilize the computational resources of field-programmable gate arrays (FPGAs) and do not extend well to full precision scenarios. To overcome these limitations, we integrate vector dot products to unify the convolution and fully connected layers. By treating the row vector of input feature maps as the fundamental processing unit, we balance processing latency and resource consumption while eliminating data rearrangement time. Furthermore, an accurate design space exploration (DSE) model is established to identify the optimal design points for each CNN layer, and dynamic partial reconfiguration is employed to maximize each layer's access to computational resources. Our approach is validated through the implementation of AlexNet and VGG16 on 7A100T and ZU15EG platforms, respectively. We achieve an average convolutional layer throughput of 28.985 GOP/s and 246.711 GOP/s for full precision. Notably, the proposed accelerator demonstrates remarkable power efficiency, with a maximum improvement of 23.989 and 15.376 times compared to current state-of-the-art FPGA implementations.

Automated Wi-Fi intrusion detection tool on 802.11 networks

Wi-Fi networks enable user-friendly network connectivity in various environments, ranging from home to enterprise networks. However, vulnerabilities in Wi-Fi implementations may allow nearby adversaries to gain an initial foothold into a network, e.g., in order to attempt further network penetration. In this paper we propose a methodology for the detection of attacks originating from Wi-Fi networks, along with a Wi-Fi Network Intrusion Detection (Wi-Fi-NID) tool, developed to automate the detection of such attacks at 802.11 networks. In particular, Wi-Fi-NID has the ability to detect and trace possible illegal network scanning attacks, which originate from attacks at the Wi-Fi access layer. We extend our initial implementation to increase the efficiency of detection, based on mathematical and statistical function techniques. A penetration testing methodology is defined, in order to discover the environmental security characteristics, related with the current configuration of the devices connected to the 802.11 network. The methodology covers known Wi-Fi attacks such as de-authentication attacks, capturing and cracking WPA-WPA/2 handshake, captive portal and WPA attacks, mostly based on various open source software tools, custom tools, as well as on specialized hardware.

Architecture and Development Framework for a Web-Based Risk Assessment and Management Platform Developed on WordPress to Address Opioid Overdose.

The number of overdose-related fatalities continues to reach historic levels across Canada, despite ongoing efforts by authorities. To reduce mortality, a clinical trajectory ranging from preventative measures to crisis intervention, skill training to treatment, and risk assessment to risk management needs to be supported. The web-based Risk Assessment and Management Platform (RAMP) was developed to realize this concept and to empower people who use drugs through an integrated tool that allows them to better understand and manage their risk of overdose. This paper outlines the architecture and development of RAMP, which is built on the WordPress platform. WordPress components are mapped onto a 3-tier architecture that consists of presentation, application, and database layers. The architecture facilitates the development of a modular software that includes several features that are independent in functionality but interact with each other in an integrated platform. The relatively low coupling and high coherence of the features may reduce the cost of maintenance and increase flexibility of future developments. RAMP's architecture comprises a user interface, conceptual framework, and backend layers. The RAMP front end effectively uses some of the WordPress' features such as HTML5, CSS, and JavaScript to create a mobile, friendly, and scalable user interface. The RAMP backend uses several standard and custom WordPress plug-ins to support risk assessment and monitoring, with the goal of mitigating the impacts and eliminating risks together. A rule-based decision support system has been hard-coded to suggest relevant modules and goals to complement each user's lifestyle and goals based on their risk assessment. Finally, the backend uses the MySQL database management system and communicates with the RAMP framework layer via the data access layer to facilitate a timely and secure handling of information. Overall, RAMP is a modular system developed to identify and manage the risk of opioid overdose in the population of people who use drugs. Its modular design uses the WordPress architecture to efficiently communicate between layers and provide a base for external plug-ins. There is potential for the current system to adopt and address other related fields such as suicide, anxiety, and trauma. Broader implementation will support this concept and lead to the next level of functionality.

Assessing the utility of SoilGrids250 for biogeographic inference of plant populations.

Inclusion of edaphic conditions in biogeographical studies typically provides a better fit and deeper understanding of plant distributions. Increased reliance on soil data calls for easily accessible data layers providing continuous soil predictions worldwide. Although SoilGrids provides a potentially useful source of predicted soil data for biogeographic applications, its accuracy for estimating the soil characteristics experienced by individuals in small-scale populations is unclear. We used a biogeographic sampling approach to obtain soil samples from 212 sites across the midwestern and eastern United States, sampling only at sites where there was a population of one of the 22 species in Lobelia sect. Lobelia. We analyzed six physical and chemical characteristics in our samples and compared them with predicted values from SoilGrids. Across all sites and species, soil texture variables (clay, silt, sand) were better predicted by SoilGrids (R 2: .25-.46) than were soil chemistry variables (carbon and nitrogen, R 2 ≤ .01; pH, R 2: .19). While SoilGrids predictions rarely matched actual field values for any variable, we were able to recover qualitative patterns relating species means and population-level plant characteristics to soil texture and pH. Rank order of species mean values from SoilGrids and direct measures were much more consistent for soil texture (Spearman r S = .74-.84; all p < .0001) and pH (r S = .61, p = .002) than for carbon and nitrogen (p > .35). Within the species L. siphilitica, a significant association, known from field measurements, between soil texture and population sex ratios could be detected using SoilGrids data, but only with large numbers of sites. Our results suggest that modeled soil texture values can be used with caution in biogeographic applications, such as species distribution modeling, but that soil carbon and nitrogen contents are currently unreliable, at least in the region studied here.

ME-MAC Protocol for MAC Layer in MANET to Overcome HET Problem

Medium Access layer in Mobile Adhoc Network is responsible of transmission of packet through the wireless medium, while transmitting the packet all nodes has to intellect the medium before sending the packet. Every node can able to transmit the packet when the medium if free otherwise the nodes have to wait until the medium becomes free. Some cases the transmission range of the node can be idle but due to Hidden and Exposed node, the node could not be sending the packet to other nodes. Node has to wait unnecessarily event the transmission medium is free. This research article proposed the Mutual Exclusion MAC protocol for avoiding hidden and exposed terminal problem in MANET. The proposed protocol is implemented with the support of Network simulator 3 and results are compared with the existing different protocol proposed for the MAC layer with the parameter and better results shown.

Construction of network access Layer security protection System based on zero trust architecture

In order to further solve the problem of weak attack defense existing in the traditional network architecture, improve the shortcomings of network architecture in processing capacity, hardware expansion, security protection and other aspects, and better cope with the security challenges under the new network architecture, this article aims to provide more secure computer information exchange and sharing services for enterprises. A network access layer security protection system based on zero trust architecture is constructed. At the same time, the zero-trust architecture evaluation algorithm based on fuzzy theory is used to construct the security protection model. System tests show that more than 100 hosts on the enterprise access layer network use switches that support SNMP, and the security protection system at the network access layer processes more than 1500 attacks. In addition, malicious IP address changes are effectively prevented and the security protection level is greatly improved.

Exploring Future Storage Options for ATLAS at the BNL/SDCC facility

Exploring Future Storage Options for ATLAS at the BNL/SDCC facility